{"id":"W4389988181","doi":"10.7202/1092628ar","title":"Auto Insurance Reform for Canada’s Tort Provinces","year":2004,"lang":"fr","type":"article","venue":"Assurances et gestion des risques","topic":"Law, Economics, and Judicial Systems","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval; University of Calgary","funders":"","keywords":"Incentive; Business; Payment; Liability; Tort; Work (physics); Limiting; Compensation (psychology); Public economics; Punitive damages; Damages; Transaction cost; Actuarial science; Finance; Economics; Microeconomics; Law; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001206603,0.0003605605,0.0009433878,0.0001439828,0.0004568312,0.0002835913,0.0004240012,0.0003574118,0.00007912146],"category_scores_gemma":[0.0003130476,0.0005125309,0.000244647,0.0002149385,0.0004992829,0.001367648,0.00004573138,0.0002523012,0.0001035001],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004085534,"about_ca_system_score_gemma":0.000895331,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8393502,"about_ca_topic_score_gemma":0.9273273,"domain_scores_codex":[0.9968311,0.0000554276,0.001408702,0.0008203658,0.00009914382,0.0007853152],"domain_scores_gemma":[0.9981062,0.000171012,0.0009124573,0.0004256646,0.0001865847,0.0001980912],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001709072,0.0003253735,0.08980126,0.001264483,0.0004307535,0.0000200107,0.001882455,0.02242602,0.000009794604,0.8139481,0.01879774,0.05092313],"study_design_scores_gemma":[0.00188059,0.0004655303,0.1631245,0.0008855339,0.00003718409,0.00003024906,0.0005786669,0.002723879,0.0004095466,0.1671827,0.6614669,0.001214639],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4573664,0.1068142,0.009491843,0.09686811,0.0244943,0.002935619,0.007189436,0.0003288337,0.2945112],"genre_scores_gemma":[0.9789016,0.009030213,0.002307614,0.0007253282,0.001066877,0.0002124288,0.00008372555,0.00007050936,0.007601659],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6467654,"threshold_uncertainty_score":0.9997376,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02991715265544547,"score_gpt":0.2361038780600701,"score_spread":0.2061867254046247,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}